Article
Version 1
Preserved in Portico This version is not peer-reviewed
Regional Differences in Energy and Environmental Performance: An Empirical Study of 283 Cities in China
Version 1
: Received: 4 June 2018 / Approved: 6 June 2018 / Online: 6 June 2018 (09:59:47 CEST)
A peer-reviewed article of this Preprint also exists.
Sun, Z.; An, C.; Sun, H. Regional Differences in Energy and Environmental Performance: An Empirical Study of 283 Cities in China. Sustainability 2018, 10, 2303. Sun, Z.; An, C.; Sun, H. Regional Differences in Energy and Environmental Performance: An Empirical Study of 283 Cities in China. Sustainability 2018, 10, 2303.
Abstract
This paper proposes a new non-radial biennial Luenberger energy and environmental performance index (EEPI) to measure the EEP change in various Chinese cities. The sources of EEP change, in terms of technical efficiency change and technological change, are examined by Luenberger EEPI. The contributions from specific undesirable outputs and energy inputs to the EEP change are identified by means of the non-radial efficiency measure. The proposed approach is applied to evaluate the EEP of the industrial sector in 283 cities in China over 2010-2014. Factors influencing the emission abatement potential are investigated by employing geographically weighted regression (GWR) model. We find that 1) changes in EEP can be attributed to technological progress but that technological progress slows down across the study period; 2) the soot emission performance experiences a downtrend among four specific sub-performances in line with the truth that severe haze happened frequently in China; 3) the best performers begin to move from the coastal to inland cities with the less resource consumption and higher ecological equality; 4) cities with the strongest positive effect in regards to pollution intensity on emission abatement potential are located in the areas around the Bohai Gulf, where air pollution is particularly severe.
Keywords
data envelopment analysis; biennial Luenberger index; geographically weighted regression; EEP
Subject
Business, Economics and Management, Economics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment